The growing demand for behavioral healthcare continues to outpace supply. Combined with the challenges people can face accessing services, this leaves many in distress without a path to timely care. Although providers and state partners are identifying policy solutions to address the shortage in the behavioral health workforce, these solutions will take time to implement and evaluate. Behavioral health providers are beginning to consider more immediate actions to increase access to care, streamline operations, save money, and improve quality and outcomes. Enter artificial intelligence (AI).
We attended this year’s NatCon—the largest national conference in mental health and substance use treatment—and saw AI-focused technology vendors, partners, and presentations everywhere. With 50 health information technology exhibitors, sessions on AI ethics and data security, and even talk of AI in keynote remarks, technology was more than a backdrop—it was a driving force that shaped conversations.
As AI solutions take center stage in behavioral healthcare, how can organizations responsibly implement it to enhance their work while protecting the safety and well-being of their clients?
Opportunities for AI in behavioral health practices
Here are some common ways organizations are incorporating AI into behavioral health practices:
- Reduce routine and compliance-related tasks. AI can apply billing codes, send reminders, or incorporate notes into electronic health records, tasks that take up time and keep practitioners from productivity and billable hours.
- Serve as a clinical enhancer. AI can quickly synthesize information from multiple data sources and aggregate and summarize a client’s history to help practitioners tailor evidence-based interventions for the problem the client presents with.
- Support diagnosis and decisions. AI-powered ambient listening devices have the ability to transcribe and recap sessions, which can make it easier for practitioners to review information and make informed decisions that may help with diagnosis, crisis management, and treatment planning.
These use cases likely only scratch the surface, but behavioral health organizations should evaluate multiple dimensions of organizational readiness before implementing any AI solution.
Considerations for AI in behavioral health
Behavioral health organizations must approach AI strategically, carefully evaluating potential solutions and their own internal capacities, resources, and supports to determine whether AI is right for them. And, if it is, they need to know which solutions they should pursue to meet their needs. Without a thorough evaluation of their readiness and the proposed solution, implementation outcomes may suffer.
To help behavioral health organizations and partners confidently navigate the complex decision-making process needed to adopt AI solutions, we developed the Readiness Guide for Behavioral Healthcare Organizations Considering AI. Grounded in research on organizational readiness for change and implementation science, this guide serves as a reflective tool to support an organization’s thoughtful, sustainable, and responsible integration of AI into practice. Organized around key domains, the guide shows organizations how to assess and revisit their readiness at various stages of the adoption and implementation journey.
Tips for using this guide to explore whether AI is right for your organization
The guide is just a starting point for assessing your organization’s readiness to adopt an AI solution. You can customize it with individualized and tailored questions to address your own unique needs and priorities. As you work through the guide, keep these key principles in mind to ensure a meaningful and accurate assessment of your organization’s readiness:
- Be honest and objective. Reflect candidly on your organization’s strengths and limitations. The guide is most useful when you approach it with transparency and a willingness to confront challenges.
- Use multiple sources of information. Don’t rely on a single perspective. Gather insight from staff feedback, leadership, data, and external information to build a comprehensive perspective of your organization’s readiness.
- Watch for biases. Aim for a well-balanced and grounded evaluation. Be mindful of response biases, social desirability, or the influence that temporary moods or pressures could hold.
- Recognize that readiness is dynamic. Organizational readiness is not a static concept, and it can evolve with changes in leadership, staffing, policy, or external conditions. Revisit the guide periodically to reassess your position and identify any changes in your organization’s readiness.
- Pause when needed. If critical factors—such as motivation, leadership support, or resources—are not in place, it’s okay to pause and regroup. Charging ahead without proper alignment can backfire, leading to poor implementation and outcomes.
- Be cautious of overpromises. Some AI solutions may present themselves as the answer to all problems. Maintain a critical lens and ensure any tool or solution aligns with your specific needs and context.
- Stay grounded in your purpose. Return to your core use case for AI and focus on freeing up your skilled professionals to deliver high-quality behavioral healthcare.
Mathematica’s team is here to support you. We work closely with states, providers, and organizations to implement evidence-based solutions that align with your goals, strengthen oversight and management, and reduce risk and cost. With deep expertise in behavioral health, data analytics, and evaluation methods, we can help you evaluate how AI might fit into your organization—and guide you through each step of the process.
